Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Stereotype Threat and Self-fulfilling Prophecies02:09

Stereotype Threat and Self-fulfilling Prophecies

37.2K
When we hold a stereotype about a person, we have expectations that he or she will fulfill that stereotype. A self-fulfilling prophecy is an expectation held by a person that alters his or her behavior in a way that tends to make it true. When we hold stereotypes about a person, we tend to treat the person according to our expectations. This treatment can influence the person to act according to our stereotypic expectations, thus confirming our stereotypic beliefs. Research by Rosenthal and...
37.2K
Hindsight Biases01:12

Hindsight Biases

3.4K
Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
3.4K
Fundamental Attribution Error01:14

Fundamental Attribution Error

12.8K
According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
12.8K
Cause and Effect01:53

Cause and Effect

10.8K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
10.8K
Self-Discrepancy Theory02:45

Self-Discrepancy Theory

18.2K
One influential perspective on what motivates people's behavior is detailed in Tory Higgin's self-discrepancy theory (Higgins, 1987). He proposed that people hold disagreeing internal representations of themselves that lead to different emotional states.  
18.2K
Self-Presentation: Self-Monitoring and Self-Handicapping02:05

Self-Presentation: Self-Monitoring and Self-Handicapping

38.6K
People can go to great lengths to protect their self-image and present themselves in ways that they want others to see them. Sociologist Erving Goffman presented the idea that a person is like an actor on a stage. Calling his theory dramaturgy, Goffman believed that we use “impression management” to present ourselves to others as we hope to be perceived. Each situation is a new scene, and individuals perform different roles depending on who is present (Goffman, 1959). Think about...
38.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Predicting deep venous thrombosis and pulmonary embolism in community patients with superficial venous thrombosis: a model development study.

Journal of thrombosis and haemostasis : JTH·2026
Same author

Individualized Treatment Effects of Therapeutic Hypothermia in Children Postcardiac Arrest: A Reanalysis of Two Randomized Clinical Trials.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies·2026
Same author

Precision-guided immunomodulatory therapy in sepsis.

The Lancet. Respiratory medicine·2026
Same author

Both Small and Large Non-aneurysmal Distal Aortic Diameters are Associated with Limb Events in Patients with Established Cardiovascular Disease.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery·2026
Same author

Clinical trials for continuously monitored and updated AI systems.

Nature medicine·2026
Same author

Missing confounding information in counterfactual prediction models: a simulation study on model-based treatment effect evaluation in radiotherapy techniques.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2026

Related Experiment Video

Updated: May 10, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

6.9K

When accurate prediction models yield harmful self-fulfilling prophecies.

Wouter A C van Amsterdam1, Nan van Geloven2, Jesse H Krijthe3

  • 1Department of Data Science and Biostatistics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University of Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.

Patterns (New York, N.Y.)
|April 23, 2025
PubMed
Summary

Medical prediction models can cause harm, acting as self-fulfilling prophecies that worsen patient outcomes. Even accurate models may be detrimental when used for clinical decision-making, necessitating a review of validation and deployment practices.

Keywords:
causal inferencedata driftdecision support techniquesdeploymentmonitoringprognosis

More Related Videos

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

8.7K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

1.9K

Related Experiment Videos

Last Updated: May 10, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

6.9K
Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

8.7K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

1.9K

Area of Science:

  • Medical Informatics
  • Clinical Decision Support
  • Health Services Research

Background:

  • Prediction models are widely adopted in healthcare for personalized, data-driven decision-making.
  • There is an expectation that these models will improve patient outcomes and inform treatment strategies.

Purpose of the Study:

  • To analyze the potential harms of using prediction models in clinical decision-making.
  • To characterize prediction models that act as harmful self-fulfilling prophecies.
  • To evaluate the utility of well-calibrated models in decision-making.

Main Methods:

  • Formal characterization of prediction models exhibiting harmful self-fulfilling prophecy behavior.
  • Analysis of model discrimination and calibration before and after deployment.
  • Theoretical evaluation of model impact on data distribution.

Main Results:

  • Prediction models can cause harm through self-fulfilling prophecies, even with good discrimination post-deployment.
  • The negative outcomes of affected patients do not reduce the model's discrimination.
  • Well-calibrated models are ineffective for decision-making as they do not alter data distribution.

Conclusions:

  • The use of prediction models in medical decision-making requires critical reassessment.
  • Standard validation and deployment practices for clinical prediction models may need revision.
  • Potential harms of self-fulfilling prophecies must be considered alongside predictive accuracy.